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Abstract:
Recent work has shown impressive transform-invariant modeling
and clustering for sets of images of objects with similar
appearance. We seek to expand these capabilities to sets of
images of an object class that show considerable variation across
individual instances (e.g. pedestrian images) using a
representation based on pixel-wise similarities,
similarity templates
. Because of its invariance to the colors of particular
components of an object, this representation enables detection of
instances of an object class and enables alignment of those
instances. Further, this model implicitly represents the regions
of color regularity in the class-specific image set enabling a
decomposition of that object class into component regions.
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